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Scheme : Discovery Projects
Research Topic : Applied Statistics
Australian State/Territory : TAS
Australian State/Territory : NSW
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  • Funded Activity

    Discovery Projects - Grant ID: DP0556068

    Funder
    Australian Research Council
    Funding Amount
    $339,658.00
    Summary
    Big-Picture Bioethics: policy-making and liberal democracy. We live an era of rapid growth in biotechnology generating new and difficult ethical questions that need to be tackled by bioethicists and politicians. This project goes beyond typical approaches in bioethics to explore the "big picture": how policies are generated in ethically-contentious domains. It is important to examine how the values of different stakeholders are reflected in such processes to ensure that they are in accordance wi .... Big-Picture Bioethics: policy-making and liberal democracy. We live an era of rapid growth in biotechnology generating new and difficult ethical questions that need to be tackled by bioethicists and politicians. This project goes beyond typical approaches in bioethics to explore the "big picture": how policies are generated in ethically-contentious domains. It is important to examine how the values of different stakeholders are reflected in such processes to ensure that they are in accordance with Australia's commitment to fostering a multicultural, pluralistic, democratic society. This project will produce practical recommendations for refining public consultation in healthcare policy-making through an examination of three relevant contentious case studies in Australia with comparison to Canada.
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    Active Funded Activity

    Discovery Projects - Grant ID: DP220102952

    Funder
    Australian Research Council
    Funding Amount
    $630,000.00
    Summary
    Artificial Intelligence, Robots, and Agriculture: Social and ethical issues. This project aims to investigate the social and ethical issues raised by the use of artificial intelligence and robotics in agriculture. By combining social science research methods and philosophical analysis, the project aims to generate new knowledge in bioethics and applied ethics. Expected outcomes of this project include an account of the social and ethical issues farmers, rural communities, and consumers anticipat .... Artificial Intelligence, Robots, and Agriculture: Social and ethical issues. This project aims to investigate the social and ethical issues raised by the use of artificial intelligence and robotics in agriculture. By combining social science research methods and philosophical analysis, the project aims to generate new knowledge in bioethics and applied ethics. Expected outcomes of this project include an account of the social and ethical issues farmers, rural communities, and consumers anticipate arising from these technologies, improved understanding of these issues, and an account of how these groups would like to see these issues addressed. This should help Australia benefit from the responsible use of artificial intelligence and robotics in agriculture.
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    Funded Activity

    Discovery Projects - Grant ID: DP180102215

    Funder
    Australian Research Council
    Funding Amount
    $338,178.00
    Summary
    An efficient approach to the computation of bacterial evolutionary distance. This project aims to apply advanced mathematical tools to improve our understanding of bacterial evolution. Bacteria account for as much total Earth biomass as all plant species put together, and have an unparalleled ability to evolve quickly and adapt to changing environments. Unfortunately, the existing mathematical models used to model bacterial evolution are generally computationally intractable. This project will r .... An efficient approach to the computation of bacterial evolutionary distance. This project aims to apply advanced mathematical tools to improve our understanding of bacterial evolution. Bacteria account for as much total Earth biomass as all plant species put together, and have an unparalleled ability to evolve quickly and adapt to changing environments. Unfortunately, the existing mathematical models used to model bacterial evolution are generally computationally intractable. This project will rectify this situation by using representation theory to transform combinatorial group theory into linear algebra, allowing for the application of advanced methods of numeric approximation. This will provide a better understanding of how bacteria evolve and improve our ability to manage their impact.
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